Variation in the whiteness and brightness of mohair associated with farm, season, and mohair attributes

This work aimed to quantify factors affecting the reflectance attributes of Australian white mohair sourced from five different farms and to evaluate the effect of season and year on mohair grown by goats of known genetic origin in a replicated study. For the season study the mohair was harvested every three months for two years. All goats and their fleeces were weighed. Mid-side samples were tested for fibre diameter attributes, clean washing yield (CWY), staple length (SL) and for tristimulus values X, Y, Z and Y-Z. For the farm study (n = 196), linear models, relating Y, Z and Y-Z were fitted to farm of origin and other objective measurements. For the season and year study (n = 176), data were analysed by ANOVA and then by linear analysis. The variation accounted for by farm alone was: X, 22%; Y, 24%; Z, 12%; Y-Z, 30% (P < 0.001). Once farm had been taken into account, the regression models for X, Y and Z had similar significant terms: mean fibre diameter (MFD), CWY, SL and fibre diameter CV; and correlation coefficients (057–0.65). For Y-Z, in addition to farm only MFD was significant (P = 1.8 × 10−9). While X, Y, Z and Y-Z were significantly associated with clean fleece weight (CFwt), CFwt was not significant in any final model. Season affected mohair Y (P = 2.5 × 10−24), Z (P = 2.3 × 10−20) and Y-Z (P = 6.8 × 10−22). Autumn grown mohair had higher Y and Z, and summer grown mohair had lower Z than mohair grown in other seasons. This resulted in summer grown mohair having the highest Y-Z and winter grown mohair having the lowest Y-Z than mohair grown in other seasons. The differences between years in Y, Z and Y-Z were significant but not large. When Y, Z and Y-Z were modeled with season and other mohair attributes, MFD, CWY, CFwt, incidence of medullated fibre (Med) and sire were also significant terms. This model accounted for 62.1% of the variance. Over the range of Med (0.3–4.2%), Y-Z increased by 11 T units. Increasing CFwt 0.5 kg was associated with a decline in Y-Z of 7.5 T units. The variation in Y, Z and Y-Z associated with sire effects were respectively 2.66, 3.77, and 1.04 T units. In the farm and the season studies increasing MFD was associated with lower Y and Z and higher Y-Z. The extent of the differences in tristimulus values between seasons and years, were unlikely to be of commercial importance. The extent of the differences between farms, and to variations in MFD and Med were large enough to be of commercial importance. Clean mohair colour was artefactually biased by MFD.

Voluntary demand for auditing by farm businesses: an Australian perspective

 This study investigates voluntary demand for auditing by Australian farm businesses, a significant but relatively unexplored segment of the economy. Most farms operate as family partnerships or sole proprietors and we thus focus on incentives to audit arising from internal sources (owner-manager), controlling for traditional incentives arising from external contractual constraints (i.e., debt), organisational characteristics (i.e., size), and agency conflict. We hypothesise that an external audit assists management in enhancing internal control by complementing the process of profit planning and control (budgeting) and that increased family conflict provides an incentive to engage external audit. Of the 457 survey questionnaire respondents, 27% voluntarily engage an external auditor and 66% conduct some formal written planning. Results from logistic regression analyses support the predicted impact of both size and debt on audit, and further support the hypothesised impact of budgeting. The positive association between budgeting and audit confirms the complementary relationship. More importantly, this relationship is not confounded by the combined impact of size and budgeting and debt and budgeting on voluntary audit. In addition, family conflict has no impact on voluntary demand for auditing by farm business.

Prediction intervals for short-term wind farm power generation forecasts

Quantification of uncertainties associated with wind power generation forecasts is essential for optimal management of wind farms and their successful integration into power systems. This paper investigates two neural network-based methods for direct and rapid construction of prediction intervals (PIs) for short-term forecasting of power generation in wind farms. The lower upper bound estimation and bootstrap methods are used to quantify uncertainties associated with forecasts. The effectiveness and efficiency of these two general methods for uncertainty quantification is examined using twenty four month data from a wind farm in Australia. PIs with a confidence level of 90% are constructed for four forecasting horizons: five, ten, fifteen, and thirty minutes. Quantitative measures are applied for objective evaluation and unbiased comparison of PI quality. Demonstrated results indicate that reliable PIs can be constructed in a short time without resorting to complicate computational methods or models. Also quantitative comparison reveals that bootstrap PIs are more suitable for short prediction horizon, and lower upper bound estimation PIs are more appropriate for longer forecasting horizons.

Depression, anxiety and metabolic syndrome in farm men and women

This research found that Depression was associated with the development of metabolic syndrome, whilst both Depression and Anxiety are associated with the maintenance of metabolic syndrome in Farm men and women. Future interventions in metabolic syndrome should consider screening for and treating these psychological factors to improve health outcomes.

Assessing the impact of HRM on dairy farm performance: an Australian study

This thesis explains the benefits of HRM policies and practices for Australian dairy farmers. A conceptual roadmap for rural industry policy-makers and farm owner-managers is presented in this thesis. It helps farmers to enhance dairy farm performance through HRM practices, which in turn would contribute to regional economic development.